A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain.

This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore, monitoring system synchronization via the EEG signal is unlikely to give advanced warning of imminent seizure activity. Through simulation, it is shown that synchronization tracking may still be viable using an input probing stimulus to actively seek information from the coupled oscillator network.